Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information);Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Use social media;Do arts and crafts;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Generic chatbot conversation;Solving math or logical problems;Generate art;Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Creative or artistic;Personal;Learning 
Prompt 1: Can you create a colour image of a thistle, a red rose and two blue roses entwinned for a memorial tattoo
Prompt 2: what problems do ferries have when trying to dock in windy weather
Prompt 3: at what wind speed do UK ferries tend not to sail?
Prompt 4: what actually is hrt?
Prompt 5: Can I work on a local committee as well as representing the locality as a parish councillor?
Prompt 6: Does the NHS trust employ people over the age of 60?
Prompt 7: What hairstyle would suit me? I have a fat face, over 60 and don't like wasting time styling my hair?
Prompt 8: What is the best way to learn mathematics, fractions, algebra etc.?
Prompt 9: Where is the best online site that do free e-courses with certificates at the end?
Prompt 10: Can you draw a marginated tortoise?
Comments: I have input to the best of my knowledge my most recent prompts to my Chatgpt.